In silico, in vivo enzymatic, non-enzymatic toxicity and antioxidant activity of a heterocyclic compound: 5-Benzyl -1, 3, 4-oxadiazole-2-thiol, a potential drug candidate.

The present study aimed to investigate the enzymetic, non-enzymetic toxicity and antioxidant potential of a drug candidate 5-Benzyl-1,3,4-Oxadiazole-2-Thiol(OXPA) using computational tools and in vivo models. The binding pattern of it, with different toxicity/oxidative enzymes was predicted using software pkCSM, Protox- II, LAZAR, Mcule 1-Click Docking 3D-Ligand binding Site and best score obtained used as an evaluating criterion. After acute oral toxicity, in vivo. antioxidant and hepato protective activity was investigated on male wistar rats, segregated into four groups as control (NS), toxic (INH-RIF), standard (Silymerin) and sample (OXPA, 100mg/Kg) for 21days. Level of antioxidant enzymes / histopathology and serum biochemical parameters in liver and blood of treated rats was assessed by using scientific tools. In silico study reveal no profound toxicity parameters however, LD50 found to be 560mg/Kg while in vivo study declared it safe till 1000mg/Kg, as having no toxicity symptoms. Molecular interaction score with GTH reductase, s-transferase and significant in vivo antioxidant effect on catalase, SOD, TBARS enzymes and histopathological assessment, declare OXPA a good antioxidant having significant (P< 0.05) hepato protective activity. Results of in silico, in vivo studies declare the propensity of 5-Benzyl-1, 3, 4-oxadiazole-2-thiol as potential antioxidant, for further investigations as a drug.

Prognostic Modeling and Prevention of Diabetes Using Machine Learning Technique.

Stratifying individuals at risk for developing diabetes could enable targeted delivery of interventional programs to those at highest risk, while avoiding the effort and costs of prevention and treatment in those at low risk. The objective of this study was to explore the potential role of a Hidden Markov Model (HMM), a machine learning technique, in validating the performance of the Framingham Diabetes Risk Scoring Model (FDRSM), a well-respected prognostic model. Can HMM predict 8-year risk of developing diabetes in an individual effectively? To our knowledge, no study has attempted use of HMM to validate the performance of FDRSM. We used Electronic Medical Record (EMR) data, of 172,168 primary care patients to derive the 8-year risk of developing diabetes in an individual using HMM. The Area Under Receiver Operating Characteristic Curve (AROC) in our study sample of 911 individuals for whom all risk factors and follow up data were available is 86.9% compared to AROCs of 78.6% and 85% reported in a previously conducted validation study of FDRSM in the same Canadian population and the Framingham study respectively. These results demonstrate that the discrimination capability of our proposed HMM is superior to the validation study conducted using the FDRSM in a Canadian population and in the Framingham population. We conclude that HMM is capable of identifying patients at increased risk of developing diabetes within the next 8-years.

A Hybrid Approach for Modeling Type 2 Diabetes Mellitus Progression.

Type 2 Diabetes Mellitus (T2DM) is a chronic, progressive metabolic disorder characterized by hyperglycemia resulting from abnormalities in insulin secretion, insulin action, or both. It is associated with an increased risk of developing vascular complication of micro as well as macro nature. Because of its inconspicuous and heterogeneous character, the management of T2DM is very complex. Modeling physiological processes over time demonstrating the patient's evolving health condition is imperative to comprehending the patient's current status of health, projecting its likely dynamics and assessing the requisite care and treatment measures in future. Hidden Markov Model (HMM) is an effective approach for such prognostic modeling. However, the nature of the clinical setting, together with the format of the Electronic Medical Records (EMRs) data, in particular the sparse and irregularly sampled clinical data which is well understood to present significant challenges, has confounded standard HMM. In the present study, we proposed an approximation technique based on Newton's Divided Difference Method (NDDM) as a component with HMM to determine the risk of developing diabetes in an individual over different time horizons using irregular and sparsely sampled EMRs data. The proposed method is capable of exploiting available sequences of clinical measurements obtained from a longitudinal sample of patients for effective imputation and improved prediction performance. Furthermore, results demonstrated that the discrimination capability of our proposed method, in prognosticating diabetes risk, is superior to the standard HMM.

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression.

Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screening is complicated by the fact that the accuracy of noninvasive testing lacks specificity and sensitivity to make and stage the diagnosis. Currently no non-invasive ATP III criteria based prediction method is available to diagnose NAFLD risk. Firstly, the objective of this research is to develop machine learning based method in order to identify individuals at an increased risk of developing NAFLD using risk factors of ATP III clinical criteria updated in 2005 for Metabolic Syndrome (MetS). Secondly, to validate the relative ability of quantitative score defined by Italian Association for the Study of the Liver (IASF) and guideline explicitly defined for the Canadian population based on triglyceride thresholds to predict NAFLD risk. We proposed a Decision Tree based method to evaluate the risk of developing NAFLD and its progression in the Canadian population, using Electronic Medical Records (EMRs) by exploring novel risk factors for NAFLD. Our results show proposed method could potentially help physicians make more informed choices about their management of patients with NAFLD. Employing the proposed application in ordinary medical checkup is expected to lessen healthcare expenditures compared with administering additional complicated test.

Preliminary phytochemical analysis and in vivo evaluation of antipyretic effects of hydro-methanolic extract of Cleome scaposa leaves.

Cleome scaposa has been associated with the prevention of many diseases as fever, abdominal complaints and cancer. But its antipyretic effect is not reported so far. The aim of this study was to assess the efficacy of C. scaposa in reducing temperature in Baker's yeast-induced fever model of rabbits. Rabbits were randomized into 4 groups (n = 24). Fever was induced in by Saccharomyces cerevisae (3 mL/kg of 10% suspension subcutaneous) in all study groups. Afterward, group 1, 2, 3 and 4 were orally administered with paracetamol 150 mg/kg b. wt., distilled water, C. scaposa 250 and 500 mg/kg b. wt. respectively. 500 mg/kg dosage was selected after dose fixation study. The standard control was paracetamol. Rectal temperature was recorded with the help of a digital thermometer. ANOVA followed by post hoc test was applied for statistical analysis of results. Results of the study indicate that C. scaposa possesses antipyretic activity comparable to that of standard drug paracetamol as it exhibited comparable antipyretic potential against baker's yeast-induced fever in rabbits. This study confirms the traditional use of C. scaposa in fever. So, it can be an alternative therapeutic choice in fever. However, specific constituents responsible for its antipyretic activity should be evaluated.

Toxic metal interactions affect the bioaccumulation and dietary intake of macro- and micro-nutrients.

The present study was conducted to evaluate the effects of heavy metals (cadmium (Cd), lead (Pb) and Cd-Pb mix) on bioaccumulation of different nutrients. Three plant species including potato, tomato and lettuce were grown in pots containing soil contaminated with Cd, Pb and Cd-Pb mix at four different levels. The edible portions of each plant were analysed for Cd, Pb and different macro- and micro-nutrients including protein, vitamin C, nitrogen (N), phosphorous (P), potassium (K), iron (Fe), manganese (Mn), calcium (Ca) and magnesium (Mg). Results indicated significant variations in selected elemental concentrations in all the three plants grown in different treatments. The projected daily dietary intake values of selected metals were significant (P < 0.001) for Fe, Mn, Ca and Mg but not significant for protein, vitamin C, N and P. The elemental contribution to Recommended Dietary Allowance (RDA) was significant for Mn. Similarly, Fe and Mg also showed substantial contribution to RDA, while Ca, N, P, K, protein and vitamin C showed the minimal contribution for different age groups. This study suggests that vegetables cultivated on Cd and Pb contaminated soil may significantly affect their quality, and the consumption of such vegetables may result in substantial negative effects on nutritional composition of the consumer body. Long term and continuous use of contaminated vegetables may result in malnutrition.

Comparative study of heavy metals in dried and fluid milk in Peshawar by atomic absorption spectrophotometry.

Various essential and toxic heavy metals (Ca, Mg, Cu, Zn, Fe, Mn, Pb, Cd, Cr, and Ni) contents in various types of dried (infant formula and powdered) and fluid (fresh and processed) cow milk were assessed by atomic absorption spectrophotometry. The milk samples were collected from local markets of different parts of Peshawar city, Pakistan. Heavy metal concentrations varied significantly depending upon the type of milk. The heavy metal concentrations in most of the samples were within normal and permissible ranges. It was observed that the samples contained considerable amounts of calcium, while magnesium levels were well above the required levels. The results also revealed that copper levels were slightly lower than the permissible limits. The concentration of zinc in dried milk samples was greater than the values for the liquid milk types. Infant milk formulae had higher iron levels as compared to other milk samples because of the added constituents. Significant differences were observed in the mean values of manganese and cadmium in different types of milk. The toxic metals were within the acceptable limits and did not show significant levels leading to toxicity.

Reproductive and sexual health issues: knowledge, opinion and attitude of medical graduates from Karachi.

OBJECTIVES: To asses the knowledge, opinion and attitude of medical graduates regarding selected reproductive tract infections, diagnosis of sexual dysfunction, identification of sexual abuse and other sexual health issues in Fatima Baqai Hospital Gadap Town. METHODS: A cross sectional study conducted from January 2009 to July 2009 in Fatima Baqai Hospital Karachi. An anonymous, self administrated structured questionnaire was completed by medical graduates. Formal/informal interviews were also arranged. The questionnaire and interviews addressed socio-demographic features, reproductive problems knowledge, attitudes and experience of those medical graduates. Descriptive statistics were analyzed by SPSS version 11. RESULT: A total of 50 medical graduates participate in the study. Of the total nearly half scored less than 50% in the knowledge section. Attitude and practices assessment suggested a tendency to be judgmental, gender/rights discriminatory and with little provision for enabling clients to make their own decision, so essential for quality sexual health provision. CONCLUSION: The level of reproductive and sexual health knowledge among the participant medical graduates were lower than expected. Attitudes and opinions indicate judgmental approach and indicating lack of experience of training in dealing with sexuality issues.

Mould incidence and mycotoxin contamination in maize kernels from Swat Valley, North West Frontier Province of Pakistan.

Mould incidence and aflatoxin B1 (AFB1) and ochratoxin A (OTA) contamination as well as proximate composition and minerals content of maize kernels from Swat Valley, North West Frontier Province of Pakistan was studied during the year, 2007. Results indicated that the mean moisture content of the kernels was within the recommended safe storage levels of 15%. Across the whole valley, Aspergillus, Fusarium, Penicillium and Rhizopus were the most predominant fungal genera identified and amongst the mycotoxigenic species, Aspergillus flavus had the highest incidence. AFB1 content ranged from none to 30.92 microg/kg with the average values of 14.94 and 16.22 microg/kg for Upper and Lower Swat regions, respectively. Similar trend was observed for OTA with the contamination level ranged from <0.001 to 7.32 microg/kg. A significant numbers of samples contained AFB1 and OTA levels above the safe limits as recommended by the USFDA and EU but on the average the results were within the safe limit. These results indicate that maize consumers in Swat Valley may be exposed to the danger of aflatoxins and ochratoxins poisoning. Thus, there is a need for policy makers to establish and enforce maize quality standards and regulations related to moulds and mycotoxins across the area.